Modelling mangrove propagule dispersal trajectories using high‐resolution estimates of ocean surface winds and currents

Abstract

Mangrove forests are systems that provide ecosystem services and rely on floating propagules of which the dispersal trajectories are determined by ocean currents and winds. Quantitating connectivity of mangrove patches is an important conservation concern. Current estimates of connectivity, however, fail to integrate the link between ocean currents at different spatial scales and dispersal trajectories. Here, we use high-resolution estimates of ocean currents and surface winds from meteorological and oceanographic analyses, in conjunction with experimental data on propagule traits (e.g., density, size, and shape) and dispersal vector properties (e.g., strength and direction of water and wind currents). We incorporate these data in a dispersal model to illustrate the potential effect of wind on dispersal trajectories of hydrochorous propagules from different mangrove species. We focus on the Western Indian Ocean, including the Mozambique Channel, which has received much attention because of its reported oceanic complexity, to illustrate the effect of oceanic features such as eddy currents and tides. In spite of the complex pattern of ocean surface currents and winds, some propagules are able to cross the Mozambique Channel. Eddy currents and tides may delay arrival at a suitable site. Experimentally demonstrated differences in wind sensitivity among propagule types were shown to affect the probability of departure and the shape of dispersal trajectories. The model could be used to reconstruct current fluxes of mangrove propagules that may help explain past and current distributions of mangrove forests and assess the potential for natural expansion of these forests.Abstract in Dutch is available with online material.

A general framework for propagule dispersal in mangroves

“…Indeed, nearshore currents can be temporally dynamic, strongly non‐linear, and spatially complicated, and have been shown to result in complex dispersal and connectivity patterns (Siegel et al , ) and a population genetic structure that cannot be explained by traditional and straightforward isolation‐by‐distance models (White et al , ; Thomas et al , ). In addition, oceanic features such as tidal ellipses and meso‐ and submesoscale eddies have the potential to retain propagules (Condie & Condie, ; Van der Stocken & Menemenlis, ) and limit the spatial scale of propagule transport (Pineda et al , ), while frontal zones between mesoscale eddies might create pathways for biological transport as hypothesized by Hancke, Roberts & Ternon ().…”

“…Methodological approaches used to obtain qualitative and quantitative data on mangrove dispersal and connectivity. Images for ‘hydrodynamic and weather forecast model output’ and ‘dispersal simulation models’ are from Van der Stocken & Menemenlis ().…”

“…Lagrangian particle‐tracking models have been employed for a wide range of applications, including trajectory simulations of oil droplets from oil spills (Paris et al , ), near‐shore and deep‐sea larvae (Siegel et al , ; Mitarai et al , ; Watson et al , ; Young et al , ), marine plastics (Lebreton, Greer & Borrero, ), and to estimate potential connectivity in coral reefs (James et al , ; Cowen et al , ; Paris, Chérubin & Cowen, ; Treml et al , ; Paris et al , ; Wood et al , ). For passive mangrove propagule dispersal, this approach has been used to explain the colonization of disused shrimp ponds (Di Nitto et al , ), the effect of local dynamics and habitat distributions on the spread of mangroves (Hamilton, Osman & Feller, ), population genetic structure (Ngeve et al , ), and to study the likely impact of winds on the dispersal trajectories of propagules from different species (Di Nitto et al , ; Van der Stocken & Menemenlis, ). Recently, a high‐resolution, eddy‐ and tide‐resolving numerical ocean model has been used to simulate mangrove propagule dispersal and estimate patterns of connectivity between sites globally (Van der Stocken et al , ).…”

Short‐distance barriers affect genetic variability of Rhizophora mangle L. in the Yucatan Peninsula

“…Tall and scrub populations of R. mangle showed significant genetic differences that could be caused by their contrasting environments within a site ( (Tonné, Beeckman, Robert, & Koedam, 2017;Van der Stocken & Menemenlis, 2017;Van der Stocken et al, 2015). This suggests that scrub populations have more limited dispersion, which promotes genetic differentiation within a site (Table 4).…”

Genetic structures across a biogeographical barrier reflect dispersal potential of four Southeast Asian mangrove plant species

“…Second, as all mangroves are hydrochorous (i.e. water-dispersed), dispersal is governed by the same extrinsic factor across species, for example, oceanographic condition (Van der Stocken & Menemenlis, 2017). Thus, any disparity in the genetic connectivity across species is most likely owing to species-specific ecological and biological factors alone.…”